Spectroscopic applications are characterized by the constant effort to combine high spectral resolution with large bandwidth. A trade-off typically exists between these two aspects, but the recent development of super-resolved spectroscopy techniques is bringing new opportuni- ties into this field. This is particularly relevant for all applications where compact and cost-effective instruments are needed such as in sensing, quality control, environmental monitoring, or biometric authentication, to name a few. These unconventional approaches exploit several strategies for spectral investigation, taking advantage of concepts such as sparse sampling, artificial intelligence, or post-processing reconstruction algorithms. In this Perspective, we discuss the main strengths and weaknesses of these methods, tracing promising future directions for their further development and widespread adoption.

Perspectives and recent advances in super-resolution spectroscopy: Stochastic and disordered-based approaches / Boschetti A.; Pattelli L.; Torre R.; Wiersma D.S.. - In: APPLIED PHYSICS LETTERS. - ISSN 0003-6951. - STAMPA. - 120:(2022), pp. 250502.250502-250502.250502. [10.1063/5.0096519]

Perspectives and recent advances in super-resolution spectroscopy: Stochastic and disordered-based approaches

Boschetti A.;Pattelli L.;Torre R.;Wiersma D. S.
2022

Abstract

Spectroscopic applications are characterized by the constant effort to combine high spectral resolution with large bandwidth. A trade-off typically exists between these two aspects, but the recent development of super-resolved spectroscopy techniques is bringing new opportuni- ties into this field. This is particularly relevant for all applications where compact and cost-effective instruments are needed such as in sensing, quality control, environmental monitoring, or biometric authentication, to name a few. These unconventional approaches exploit several strategies for spectral investigation, taking advantage of concepts such as sparse sampling, artificial intelligence, or post-processing reconstruction algorithms. In this Perspective, we discuss the main strengths and weaknesses of these methods, tracing promising future directions for their further development and widespread adoption.
120
250502
250502
Boschetti A.; Pattelli L.; Torre R.; Wiersma D.S.
File in questo prodotto:
File Dimensione Formato  
BoschettiAPL2022_accepted.pdf

accesso aperto

Tipologia: Pdf editoriale (Version of record)
Licenza: DRM non definito
Dimensione 982 kB
Formato Adobe PDF
982 kB Adobe PDF Visualizza/Apri

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2158/1286460
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact